Industrial controllers are special-purpose computers utilized for controlling industrial processes, manufacturing equipment, and other factory automation, such as data collection or networked systems. In accordance with a control program, the industrial controller, having an associated processor (or processors), measures one or more process variables or inputs reflecting the status of a controlled system, and changes outputs effecting control of such system. The inputs and outputs may be binary, (e.g., on or off) as well as analog inputs and outputs assuming a continuous range of values.
Measured inputs received from such systems and the outputs transmitted by the systems generally pass through one or more input/output (I/O) modules. These I/O modules serve as an electrical interface to the controller and may be located proximate or remote from the controller including remote network interfaces to associated systems. Inputs and outputs may be recorded in an I/O table in processor memory, wherein input values may be asynchronously read from one or more input modules and output values written to the I/O table for subsequent communication to the control system by specialized communications circuitry (e.g., back plane interface, communications module). Output modules may interface directly with one or more control elements, by receiving an output from the I/O table to control a device such as a motor, valve, solenoid, amplifier, and the like.
Industrial control systems have enabled modern factories to become partially or completely automated in many circumstances. These systems generally include a plurality of Input and Output (I/O) modules that interface at a device level to switches, contactors, relays and solenoids along with analog control to provide more complex functions such as Proportional, Integral and Derivative (PID) control as stated supra. Communications have also been integrated within the systems, whereby many industrial controllers can communicate via network technologies such as Ethernet, Control Net, Device Net or other network protocols and also communicate to higher level computing systems. Generally, industrial controllers utilize the aforementioned technologies along with other technology to control, cooperate and communicate across multiple and diverse applications.
In addition, conventional control systems employ a large array of varied technologies and/or devices to achieve automation of an industrial environment, such as a factory floor or a fabrication shop. Systems employed in an automated environment can utilize a plurality of sensors and feedback loops to direct a product through, for example, an automated assembly line. Such sensors can include temperature sensors (e.g., for determining a temperature of a steel bar that is entering a roller device to press the bar into a sheet . . . ), pressure sensors (e.g., for determining when a purge valve should be opened, for monitoring pressure in a hydraulic line . . . ), proximity sensors (e.g., for determining when an article of manufacture is present at a specific device and/or point of manufacture . . . ), etc.
Proximity sensors are available in a wide variety of configurations to meet a particular user's specific sensing needs. For example, sensors can be end-mounted in a housing, side-mounted in a housing, etc., to facilitate mounting in confined spaces while permitting the sensor to be directed toward a sensing region as deemed necessary by a designer. Additionally, proximity sensors are available with varied sensing ranges, and can be shielded or unshielded. Shielded inductive proximity sensors can be mounted flush with a surface and do not interfere with other inductive proximity sensors, but have diminished sensing range when compared with unshielded proximity sensors.
Various types of proximity sensors are used for detecting the presence or absence of an object. Common types of non-contact proximity sensors include inductive proximity sensors, capacitive proximity sensors, ultrasonic proximity sensors, and photoelectric sensors. Such sensors, for example, may be used in motion or position applications, conveyor system control applications, process control applications, robotic welding applications, machine control applications, liquid level detection applications, selecting and counting applications, as well as other known applications.
In a photoelectric sensor (e.g., optoelectronic sensory, and/or photocell), for example, basic optic functions can be utilized for common object detection (e.g., through beam, retroreflex, and proximity). In one example, a photoelectric sensor includes basic elements such as, for example, a photo-emitter, an optic system, a photo-receiver, a demodulator-amplifier, a comparator, and a transistor. The photo-emitter converts a modulated electric signal into luminous energy pulses that are distinct from other light sources. The photo-emitter and a receiver can be connected in an optic system by, for example, a light beam wherein variations are elaborated to detect an object. The received luminous energy is converted into an electronic signal by, for example, a photo-receiver. After the conversion, a demodulator-amplifier extracts and amplifies part of the signal originated by the modulated light emitter. The comparator can compare the received signal and a switching threshold. Furthermore, a transistor or relay power output drives an external actuator to direct the load.
However, there is a trend in industrial technology to replace traditional mechanical gauging or sensor technology with cost-saving, easy-to-use vision sensors. A single vision sensor can supersede measurement sensors, proximity, and photoelectric sensor arrays, and/or mechanical gauges in performing inspection /measurement. For example, a vision sensor can be, but not limited to, a low end vision system, a vision camera, camera sensor, and/or smart camera. General benefits of vision sensors over traditional mechanical gauging and sensor technology include lower costs for installation, calibration, and maintenance; online accessibility to add new inspections and/or measurement capabilities; quality and efficiency; and improved functionality.
Typically, vision sensors are available in two hardware configurations—an all-in-one “smart camera” or a remote camera. The smart camera is a standalone unit where a light source, lens, camera, and processor/controller are in a single package. In contrast, the remote camera is a separate unit containing a remote camera, lens, and light source while an associated processor/controller is separately contained. The smart camera can act as a standalone unit with I/O or communication outputs and give a slight increase in speed in comparison to the remote camera based upon a lack of cable transmission for the processor/controller; however, the remote camera is more compact and can locate I/O wiring in a controller housing separate from the remote camera.
Furthermore, each hardware configuration provides associated software in order to mitigate setup and configuration costs and inefficiencies. Traditional software utilizes a pushbutton interface in order to “teach” a sensor bad and/or good machined parts, thereby allowing self-contained configuration. For example, the pushbutton interface is utilized to teach the vision sensor pattern matching, presence/absence of a pattern, and/or feature comparison, wherein the pushbutton designates a “perfect model” to which a pass or fail judgment is made. Another self-contained configuration mode utilizes a drop-down menu or interface, thereby allowing customized configuration capability for individual settings or changes tailored to each measurement and/or inspection. Regardless of the configuration mode and/or interface chosen, pass or fail determinations are simply binary without extrinsic or correlated data.
In view of the above, there is a need to improve upon and/or provide systems and/or methods relating to vision sensors and associated low end vision systems that facilitate inspecting and/or measuring within industrial manufacturing applications.